Results 11 to 20 of about 5,938,476 (293)
Low-depth optical neural networks
Chip, 2022 Optical neural network (ONNs) are emerging as attractive proposals for machine-learning applications. However, the stability of ONNs decreases with the circuit depth, limiting the scalability of ONNs for practical uses.
Xiao-Ming Zhang, Man-Hong Yung
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A Review of Optical Neural Networks
Applied Sciences, 2022 With the continuous miniaturization of conventional integrated circuits, obstacles such as excessive cost, increased resistance to electronic motion, and increased energy consumption are gradually slowing down the development of electrical computing and ...
Danni Zhang, Zhongwei Tan
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Genetically programmable optical random neural networks
Communications PhysicsToday, machine learning tools, particularly artificial neural networks, have become crucial for diverse applications. However, current digital computing tools to train and deploy artificial neural networks often struggle with massive data sizes and high ...
Bora Çarpınlıoğlu, Uğur Teğin
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Implementation of Pruned Backpropagation Neural Network Based on Photonic Integrated Circuits
Photonics, 2021 We demonstrate a pruned high-speed and energy-efficient optical backpropagation (BP) neural network. The micro-ring resonator (MRR) banks, as the core of the weight matrix operation, are used for large-scale weighted summation.
Qi Zhang, Zhuangzhuang Xing, Duan Huang
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Opto-Electronic Hybrid Network Based on Scattering Layers
Sensors, 2023 Owing to the disparity between the computing power and hardware development in electronic neural networks, optical diffraction networks have emerged as crucial technologies for various applications, including target recognition, because of their high ...
Jiakang Zhu +4 more
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Optical neural networks: The 3D connection [PDF]
Photoniques, 2020 We motivate a canonical strategy for integrating photonic neural networks (NN) by leveraging 3D printing. Our belief is that a NN’s parallel and dense connectivity is not scalable without 3D integration. 3D additive fabrication complemented with photonic signal transduction can dramatically augment the current capabilities of 2D CMOS and integrated ...
Dinc, Niyazi Ulas +2 more
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Single-shot optical neural network
Science Advances, 2023 Analog optical and electronic hardware has emerged as a promising alternative to digital electronics to improve the efficiency of deep neural networks (DNNs). However, previous work has been limited in scalability (input vector lengthK≈ 100 elements) or has required nonstandard DNN models and retraining, hindering widespread adoption.
Liane Bernstein +5 more
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Adaptive Photochemical Nonlinearities for Optical Neural Networks
Advanced Intelligent Systems, 2023 Optical neural networks (ONNs) hold great potential for faster and more energy‐efficient information processing in coherent photonic circuits. To realize ONNs, linear combinations and nonlinear activation functions have to be implemented in an optical ...
Marlon Becker +5 more
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Adversarial Attacks on an Optical Neural Network
IEEE Journal of Selected Topics in Quantum Electronics, 2023 Adversarial attacks have been extensively investigated for machine learning systems including deep learning in the digital domain. However, the adversarial attacks on optical neural networks (ONN) have been seldom considered previously. In this work, we first construct an accurate image classifier with an ONN using a mesh of interconnected Mach-Zehnder
Shuming Jiao, Ziwei Song, Shuiying Xiang
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Medical imaging analysis with artificial neural networks [PDF]
, 2010 Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection ...
Jiang, J., Ren, Jinchang, Trundle, P.
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